The purpose of this study is to examine cross-national differences in students' exploration strategies in a computer-simulated CPS (complex problem-solving) environment and to identify similarities and qualitative differences in the way Hungarian and Chinese students explore a CPS environment. In a sample of 187 Chinese and 835 Hungarian students (aged 12), we administered problem-solving items via the eDia platform within the MicroDYN approach. After structuring and coding the logfile data, latent class analyses were used to identify students whose problem-solving strategies showed similar patterns. Results indicated that Chinese students employed the most effective and successful exploration strategy, the VOTAT (vary-one-thing-at-a-time) strategy, more frequently and effectively than Hungarian students and that they showed a significantly higher learning effect during testing than their Hungarian peers. These results highlight the possibilities and importance of explicit enhancement of exploration strategies as a tool for learning in a new technological context.
The objectives of the study is to explore the applicability of online assessment for detecting the component skills of problem solving and defining factors which impact the developmental level of student's problem solving skills in China. The sample of the pilot study was drawn from six grade students (age 11-13, N=50). The instruments of the study were conducted by four tests measuring problem solving, inductive reasoning, working memory and creativity, and a questionnaire, which focused on participants' demographic data, learning strategies, and ICT familiarity. The results and findings support the views that computer-based tests are applicable to measure students thinking skills and the component skills of problem solving in China at the age of 11-13, and proved the theoretical statement which is one's problem solving achievement is influenced by some specific thinking skills and background factors.
Complex problem solving (CPS) is considered to be one of the most important skills for successful learning. In an effort to explore the nature of CPS, this study aims to investigate the role of inductive reasoning (IR) and combinatorial reasoning (CR) in the problem-solving process of students using statistically distinguishable exploration strategies in the CPS environment. The sample was drawn from a group of university students (N = 1343). The tests were delivered via the eDia online assessment platform. Latent class analyses were employed to seek students whose problem-solving strategies showed similar patterns. Four qualitatively different class profiles were identified: (1) 84.3% of the students were proficient strategy users, (2) 6.2% were rapid learners, (3) 3.1% were non-persistent explorers, and (4) 6.5% were non-performing explorers. Better exploration strategy users showed greater development in thinking skills, and the roles of IR and CR in the CPS process were varied for each type of strategy user. To sum up, the analysis identified students’ problem-solving behaviours in respect of exploration strategy in the CPS environment and detected a number of remarkable differences in terms of the use of thinking skills between students with different exploration strategies.
Noise logging is a method to determine the natural noise in a well. In the actual production logging process, it is a common situation that the noise data is not continuous with depth, which can be solved by the cubic spline interpolation method. This method is a piecewise interpolation method, which fits with a three-time polynomial in each segment interval, and adds up the polynomials on all intervals to get the interpolation formula. The interpolated data points are a smooth transition with good stability. In this article, the original noise data is interpolated to continuous noise data by cubic spline interpolation method, and then evaluated by noise imaging logging, which presents good results. The cubic-spline interpolation method ensures the internal connection of noise data, and also realizes the fine description and recognition of the characteristics of the output layer. This method will provide a low-cost and effective logging evaluation method for production logging, which has a wide range of applications.
E-learning techniques are usually classified into two broad categories: synchronous and asynchronous. The core question of this research is how to combine synchronous and asynchronous techniques in e-learning software, so it can have a stronger connection with constructivist education. The benefits and drawbacks of existing e-learning software is looked at broadly. Three popular elearning packages used at the Australian National University are investigated: Adobe Connect (synchronous), Moodle and edX (asynchronous). The results of a brief survey of edX students is reported. Using the results of this work a team of students at the ANU Research School of Computer Science is now implementing enhanced asynchronous software to be plugged into Moodle and other asynchronous e-learning packages.
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